Put the ipynb file and html file in the github branch you created in the last assignment and submit the link to the commit in brightspace
from plotly.offline import init_notebook_mode
import plotly.io as pio
import plotly.express as px
init_notebook_mode(connected=True)
pio.renderers.default = "plotly_mimetype+notebook"
#load data
df = px.data.gapminder()
df.head()
| country | continent | year | lifeExp | pop | gdpPercap | iso_alpha | iso_num | |
|---|---|---|---|---|---|---|---|---|
| 0 | Afghanistan | Asia | 1952 | 28.801 | 8425333 | 779.445314 | AFG | 4 |
| 1 | Afghanistan | Asia | 1957 | 30.332 | 9240934 | 820.853030 | AFG | 4 |
| 2 | Afghanistan | Asia | 1962 | 31.997 | 10267083 | 853.100710 | AFG | 4 |
| 3 | Afghanistan | Asia | 1967 | 34.020 | 11537966 | 836.197138 | AFG | 4 |
| 4 | Afghanistan | Asia | 1972 | 36.088 | 13079460 | 739.981106 | AFG | 4 |
Recreate the barplot below that shows the population of different continents for the year 2007.
Hints:
# I did question 1, 2 and 3 at once, as said in the lecture
df_2007 = df.query('year==2007')
df_2007_group = df_2007.groupby('continent').sum()
fig = px.bar(df_2007_group, x="pop", y=df_2007_group.index, color=df_2007_group.index, text_auto='.2s')
fig.update_layout(yaxis={'categoryorder': 'total ascending'}, showlegend=False)
fig.show()
# I did question 1, 2 and 3 at once, as said in the lecture
fig = px.bar(df_2007_group, x="pop", y=df_2007_group.index, color=df_2007_group.index, text_auto='.2s')
fig.update_layout(yaxis={'categoryorder': 'total ascending'}, showlegend=False)
fig.show()
Add text to each bar that represents the population
# I did question 1, 2 and 3 at once, as said in the lecture
fig = px.bar(df_2007_group, x="pop", y=df_2007_group.index, color=df_2007_group.index, text_auto='.2s')
fig.update_layout(yaxis={'categoryorder': 'total ascending'}, showlegend=False)
fig.show()
Thus far we looked at data from one year (2007). Lets create an animation to see the population growth of the continents through the years
df_continent = df.groupby(['continent', 'year']).sum().reset_index()
fig = px.bar(df_continent, x="pop", y='continent',
animation_frame="year", animation_group='continent',
hover_name='continent', range_x=[0,4000000000],
color='continent', text_auto='.2s')
fig.update_layout(yaxis={'categoryorder': 'total ascending'}, showlegend=False)
fig.show()
Instead of the continents, lets look at individual countries. Create an animation that shows the population growth of the countries through the years
df_country = df.groupby(['country', 'year']).sum().reset_index()
fig = px.bar(df_country, x='pop', y='country', color='country',
animation_frame='year', animation_group='country',
hover_name='country', range_x=[0,1500000000])
fig.update_layout(yaxis={'categoryorder': 'total ascending'}, showlegend=False)
fig.show()
Clean up the country animation. Set the height size of the figure to 1000 to have a better view of the animation
fig = px.bar(df_country, x='pop', y='country',
animation_frame='year', animation_group='country',
hover_name='country', range_x=[0,1500000000],
color='country', height=1000)
fig.update_layout(yaxis={'categoryorder': 'total ascending'}, showlegend=False)
fig.show()
fig = px.bar(df_country, x='pop', y='country',
animation_frame='year', animation_group='country',
hover_name='country', color='country', range_x=[0,1500000000],
range_y=[len(df_country['country'].unique())-10.5, len(df_country['country'].unique())-0.5])
#0.5 is to scale the bars, so we don't get half bars in the plot
fig.update_layout(yaxis={'categoryorder': 'total ascending'}, showlegend=False)
fig.show()